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我看efficientAD里面的师生网络在训练的时候 占用了大量显存,为了降低显存,可以把前向传播前两次student网络的梯度计算属性置为false吗? 我写了一个demo代码 像下面这样: 为了 在pytorch训练这个师生网络的时候 不占显存 , 把红框中的改为绿框中的,也就是本来前向传播三次student网络,现在只保留最后一次的梯度计算属性,这样有问题吗?
The text was updated successfully, but these errors were encountered:
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我看efficientAD里面的师生网络在训练的时候 占用了大量显存,为了降低显存,可以把前向传播前两次student网络的梯度计算属性置为false吗? 我写了一个demo代码 像下面这样:
为了 在pytorch训练这个师生网络的时候 不占显存 , 把红框中的改为绿框中的,也就是本来前向传播三次student网络,现在只保留最后一次的梯度计算属性,这样有问题吗?
The text was updated successfully, but these errors were encountered: